Abstract:
Methods of recovering from disabled printer states due to the unavailability of print consumables such as toner, ink, or other colorants. Some of those methods use a conversion to a degraded format, such as process black or grayscale. Others of those methods transfer a print job to a printer that is not disabled, the print job optionally including instructions in a printer language or a metafile. A color printer capable of recovering from a disabled printer state due to the unavailability of colorants by converting a print job to a degraded format, such as true black to process black or color to grayscale printing. A printer capable of recovering from a disabled printer state due to the unavailability of colorants by forwarding a print job to another compatible printer or a print server. A system capable of recovering from a printer having unavailable colorants necessary for printing a print job including a printer and a print server, the printer forwarding the print job to the print server, the print server selecting an alternate printer and forwarding the print job thereto.
Abstract:
A camera lifting apparatus is used in an industrial vehicle equipped with a cargo handling apparatus for lifting a cargo carrying carriage up and down along a mast provided on a vehicle body. The carriage has a cargo carrying apparatus. The camera lifting apparatus comprises a camera unit attached to the cargo carrying apparatus. The camera unit has a camera for picking up an image of a work area of the cargo carrying apparatus. A moving mechanism moves the camera unit relatively to the cargo carrying apparatus. An actuator drives the moving mechanism.
Abstract:
A hybrid cascade Model-Based Predictive control (MBPC) and conventional control system for thermal processing equipment of semiconductor substrates, and more in particular for vertical thermal reactors is described. In one embodiment, the conventional control system is based on a PID controller. In one embodiment, the MBPC algorithm is based on both multiple linear dynamic mathematical models and non-linear static mathematical models, which are derived from the closed-loop modeling control data by using the closed-loop identification method. In order to achieve effective dynamic linear models, the desired temperature control range is divided into several temperature sub-ranges. For each temperature sub-range, and for each heating zone, a corresponding dynamic model is identified. During temperature ramp up/down, the control system is provided with a fuzzy control logic and inference engine that switches the dynamic models automatically according to the actual temperature. When a thermocouple (TC) temperature measurement is in failure, a software soft sensor based on dynamic model computing is used to replace the real TC sampling in its place as a control system input. Consequently, when a TC failure occurs during a process, the process can be completed without the loss of the semiconductor substrate(s) being processed.
Abstract:
The present invention provides an arbitrage control system for two or more available power sources (106, 108) that enables the automatic or manual control of one or more multi-source systems (202) to take advantage of price differentials across commodities, locations and/or time. The present invention selects a power source for a device or delivery point (110) from two or more available power sources (106, 108) by analyzing market and operational data (406). A power source (106 or 108) for the device or delivery point (110) is then selected from the two or more available power sources (106, 108) based on a set of financial parameters (408). If the device or delivery point (110) is not already connected to the selected power source, one or more signals are sent (418) to switch the device or delivery point (110) to the selected power source. The arbitrage controller (102) includes a user interface (300), market interface (302), multi-source interface (304), database (306) and processor (308). The processor (308) is communicably coupled to the user interface (300), the market interface (302), the multi-source interface (304) and the database (306).
Abstract:
A method and system of designing the operations and controls of a gas turbine, includes generating an operations model for the gas turbine including at least one objective function and defining operations and control constraints for the operations model of the gas turbine. An online dynamic optimizer/controller dynamically optimizes and controls operation of the gas turbine using model based control based on the operations model and the operations and control constraints. The model based control may include model predictive control.
Abstract:
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Abstract:
A computer system for assessing workplace hazards presents potential hazards to a user as a series of questions, which a user can select as being relevant or not to a particular task being carried out. All the data is stored in a database (10) with the different categories of hazards being associated with different work areas. Potential hazards are presented to the user and selected, if relevant. Where potential hazards are identified appropriate exposure avoidance controls are identified. A reporter generates a report setting out identified hazards and their avoidance controls. Permits and equipment data are also stored in the database and included in the report. Risk ratings are also provided for each identified risk. By providing a predefined database of hazards, avoidance controls and associated risk rating for each hazard, user subjectivity and human error are significantly reduced. In addition, the report generated by the computer system provides a mechanism for manually calculating the user-perceived risk of each hazard so that it may be contrasted with the computer-generated risk rating for that hazard. This will be of assistance for user assessment of the task to be performed and its associated risk.
Abstract:
A system and method for designing stamping tools that produce parts of desired dimensions. The system and method compensate for post stamping deviations from the desired dimensions in the shape of the tools used to produce the parts. The compensated tools result in nearly ideal parts.
Abstract:
The method and apparatus adaptively determine weighting factors within the context of an objective function for handling optimality conditions and constraints within an optimization search. The objective function is defined as a sum of credit and penalty components. The credit components represent the optimality conditions for the problem. The penalty components represent the constraint violations for the problem. Initially, each component is made up of a weight multiplied by a mathematical expression, called a term, that quantifies either an optimality condition or a constraint violation. The set of credit and penalty weights are adaptively determined based on the progress of an optimization search. Both static and dynamic representations of the modified objective function are used to perform the adaption.
Abstract:
An integrated optimization and control technique integrates an optimization procedure, such as a linear or quadratic programming optimization procedure, with advanced control, such as model predictive control, within a process plant in which the number of control and auxiliary variables can be greater than the number of manipulated variables within the process plant. The technique first determines a step response matrix defining the correlation between changes in the manipulated variables and each of the process variables that are used during optimization. A subset of the control variables and auxiliary variables is then selected to be used as inputs to a model predictive control routine used to perform control during operation of the process and a square M by M control matrix to be used by the model predictive control routine is generated. Thereafter, during each scan of the process controller, the optimizer routine calculates the optimal operating target of each of the complete set of control and auxiliary variables and provides the determined target operating points for each of the selected subset of control and auxiliary variables to the model predictive control routine as inputs. The model predictive control routine determines changes in the manipulated variables for use in controlling the process from the target and measured values for each of the subset of the control and auxiliary variables and the M by M control matrix.